System and method for waking a user up with a stimulus of varying intensity

ABSTRACT

A system is provided for waking a user up by a stimulus, wherein the stimulus is adapted to vary according to an intensity curve. A user interface is adapted to receive user preferences, such as a desired wake-up time and a preference indicator. The preference indicator indicates whether the user prefers to be more alert after waking up or to have a longer sleep. An alarm is used for providing a stimulus to the user and a processor is used for determining a stimulus intensity curve for the alarm. Determining the stimulus intensity curve is based on at least the user preferences.

CROSS-REFERENCE TO PRIOR APPLICATIONS

This application claims the benefit of European Patent Application No.19210251.5, filed on 20 Nov. 2019. This application is herebyincorporated by reference herein

FIELD OF THE INVENTION

This invention relates to the field of personalized wake-up systems. Itrelates in particular to waking a user up with a stimulus, wherein thestimulus is adapted to vary according to a stimulus intensity curvebased on user preferences.

BACKGROUND OF THE INVENTION

About one-third of a person's life is spent in sleep. Sleep is animportant rest process. The body's immune system is repaired andstrengthened during sleep, which can restore fatigued cells to normalphysiological functions and restore mental and physical strength. Aspeople's living and work pressures continue to increase, it hasseriously affected people's sleep quality. When the quality of sleep isaffected, it will affect people's health and affect people's lives andwork. Therefore, improving sleep has become an urgent need of manypeople.

Human sleep is affected by a hormone called melatonin, which is secretedby the pineal gland in the human brain. It is this hormone that guidesus to sleep and improves sleep quality. After nightfall, when lightstimulation has decreased, the secretion of melatonin in the bodyincreases. The amount of melatonin during the night directly affects thequality of sleep of a user. Light is known to have an effect onmelatonin secretion. When light intensity is diminished, the amount ofmelatonin is increased.

Based on this principle, wake-up lights are able to improve the wake-upexperience by gradually modulating light intensity and color to bringpeople to a natural wake-up and prepare the body to start the day.

Two main disadvantages of wake-up lights are usually encountered: peoplewill wake-up too early, because the light intensity is already too hightoo early or increasing too fast and people will wake-up too late,because the light intensity is not bright enough at the requestedwake-up moment or increasing too slowly.

It is also typical for an alarm to wake up the user up using sound.There are alarms which can create a volume profile for the alarm soundin order to smoothen the wake-up experience of the user. These deviceshave the same disadvantages as wake-up lights, in that users can wake uptoo early due to the volume of the alarm being too loud early on, or theuser waking up late due to the volume of the alarm being too quiet atthe desired wake-up time.

EP 2 122 420 A1 discloses a wake up stimulus control system, comprisinga control unit arranged to receive a user-determinable wake up timeinput and to control at least one stimulus source wherein the stimulussource is controllable by the control unit in such a way that thestimulus source provides a gradually increasing stimulus output independence on said input wake up time.

US 2003/095476 A1 discloses a method and apparatus for a waking systemthat wakes an individual gradually over a period of time in order topromote the wellness of that individual. The user sets the systemcontroller with a desired final wakeup time, which is the time that theuser must be awake. When the actual time reaches a stimulus introductiontime (i.e. some time prior to the desired final wakeup time), the systemcontroller causes the introduction of stimulus.

US 2018/060732 A1 discloses a method for personalized intelligentwake-up system based on multimodal deep neural network comprisesmonitoring a sleeping status of a user; obtaining a currentsleeping-stage of the user within a current time frame and a predictionof a next sleeping-stage of the user for a next time frame; correctingthe current sleeping-stage of the user through combining the currentsleeping-stage and the prediction of the next sleeping-stage;determining a wake up strategy for the current time frame.

WO 2010/035200 A1 discloses a light therapy technique includes graduallyincreasing or decreasing an intensity of light in a manner thatapproximates a change in light intensity during a natural light event,such as dawn or dusk.

US 2011/230790 A1 discloses a method for operating a sleep phaseactigraphy synchronized alarm clock that communicates with a remotesleep database, such as an internet server database, and compares userphysiological parameters, sleep settings, and actigraphy data with alarge database that may include data collected from a large number ofother users with similar physiological parameters, sleep settings, andactigraphy data.

WO 2014/057979 A1 discloses an electronic apparatus provided with analarm clock function.

WO 2019/055414 A2 discloses a stress reduction and sleep promotionsystem that includes at least one remote device and an article fortemperature conditioning a surface.

In some alarm devices, it is possible to change the settings for theintensity of the stimulus from the alarm in order to personalize thegradual increase of the stimulus. However, it is difficult for a user toknow the exact intensity curve which suits them best for certain times,as the user usually does not remember the early moments of waking up.

Therefore, there is a need for a system which can personalize thestimulus intensity curve for a user in order to optimize the userwake-up experience.

SUMMARY OF THE INVENTION

The invention is defined by the claims.

According to examples in accordance with an aspect of the invention,there is provided a system for waking a user up by a stimulus, whereinthe stimulus is adapted to vary according to an intensity curve,comprising:

a user interface adapted to receive user preferences, wherein the userpreferences comprise:

a desired wake-up time; and

a preference indicator, wherein the preference indicator indicateswhether the user prefers to be more alert after waking up or to have alonger sleep;

an alarm for providing a stimulus to the user; and

a processor for determining a stimulus intensity curve for the alarmbased on the user preferences.

A user will indicate at what time they wish to wake up, termed a desiredwake-up time, and whether they would prefer to have a longer time tosleep or feel more alert in the morning, termed a preference indicator,on a user interface. A processor then determines a stimulus intensitycurve based on the desired wake-up time and the preference indicator.

The stimulus may vary according to an intensity curve from a minimumvalue to a maximum value over a time period, wherein the processor isfor determining a suitable time period of the stimulus intensity curvebased on the user preferences.

The system may further comprise a memory unit for storing historic sleepdata of the user comprising at least historic real wake-up times andcorresponding historic intensity curves, and wherein the processor isfor determining an intensity curve for the alarm further based on thehistoric sleep data.

For example, if the user wishes to wake up at 7:15 am and has indicatedthey would prefer a longer sleep versus alertness when waking up, andthe historic data indicates that the user tends to wake up earlier than7:15 am when using a longer stimulus intensity curve, it might decide toprovide a shorter stimulus intensity curve so that the user doesn't wakeup much earlier than 7:15 am.

The user interface may be further adapted to receive as input responseto a question to determine a Karolinska Sleepiness Scale, KSS, score ofalertness of the user or other satisfaction level after waking up andstore the score in the memory unit as historic KSS data.

Determination of a stimulus intensity curve for the alarm by theprocessor may further comprise:

estimating a KSS score or other satisfaction level for the user, at thedesired wake-up time, for a plurality of reference stimulus intensitycurves based on the historic sleep data of the user;

estimating the likelihood of the user waking up earlier than the desiredwake-up time for a plurality of reference stimulus intensity curves fromthe historic sleep data; and

determining a stimulus intensity curve based on analysis of theestimated KSS scores, the estimated likelihoods and the preferenceindicator.

For example, the user interface could ask the user a pre-determinedquestion when the user wakes up to find the KSS score or alertness ofthe user. Other satisfaction level indications may be used. This datawould be stored as historic KSS data or other satisfaction data. Thehistoric data can then be used by the processor to estimate a score orlevel for the user at the desired wake-up time for different referencestimulus intensity curves. The likelihood of the user waking up earlyfor different reference stimulus intensity curves is also estimated.These estimations can then be compared against the preference indicatorto find which stimulus intensity curve matches the preference of theuser.

The alarm may be a wake-up light and the stimulus intensity curvemodulates the intensity of the light.

The stimulus intensity curve may further modulate the color of the lightemitted by the wake-up light.

The stimulus intensity curve may simulate a sunrise.

The system may further comprise at least one sensor or input device forreceiving sensor data or input data, wherein the processor is adapted touse the sensor data to determine the intensity curve, wherein the sensoror input device comprises one or more of (but not limited to):

a motion sensor for sensing when the user wakes up;

a sensor for detecting when the user falls asleep;

an ambient light sensor;

a temperature sensor;

a user input device; and

an ambient sound sensor.

The user interface may be further adapted to receive the real wake-uptime from the user. Thus, the user may provide an input to the system assoon as they wake up, to provide feedback to the system to assist inlearning the user response to different intensity curves. This may beachieved using the user input device.

The fall asleep time and wake-up time may be used to derive the sleepduration and/or the time in bed.

The system may also comprise at least one sensor for receiving sensordata, wherein the processor may be adapted to use the sensor data todetermine the stimulus intensity curve, wherein the historic sleep datafurther comprises historic sensor data. This may be used to provideautomated feedback in respect of the user's response to the intensitycurve applied to the stimulus.

The sensors could be a motion sensor for sensing when the user wakes up,an ambient light sensor, a temperature sensor or an ambient sound sensor(microphone). The data from these sensors can be used in combinationwith the historic data to find the ideal wake-up curve for the user. Forexample if the user seems to wake up as soon as a certain threshold ofambient light or ambient sound occurs, the stimulus intensity curvecould be chosen by the processor such that the threshold is not passedbefore the desired wake-up time.

The invention also provides a method for determining an intensity curvefor a stimulus to be generated by an alarm, comprising:

receiving user preferences, wherein the user preferences comprise:

a desired wake-up time; and

a preference indicator which indicates whether the user prefers to bemore alert after waking up or to have a longer sleep;

determining a stimulus intensity curve based on the user preferences.

There may additionally be modulation of sounds and colors to begenerated as the stimulus.

The invention also provides a computer program comprising computerprogram code means which is adapted, when said computer program is runon a computer, to implement the method of determining an intensity curvefor a stimulus.

These and other aspects of the invention will be apparent from andelucidated with reference to the embodiment(s) described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the invention, and to show more clearlyhow it may be carried into effect, reference will now be made, by way ofexample only, to the accompanying drawings, in which:

FIG. 1 shows a schematic representation of the system for waking a userup;

FIGS. 2A and 2B show graphical representations of the stimulus intensitycurves;

FIG. 3 shows a second schematic representation of a system for waking auser up; and

FIG. 4 shows a flow diagram of the method used by the processor todetermine a stimulus intensity curve to be generated by an alarm.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The invention will be described with reference to the Figures.

It should be understood that the detailed description and specificexamples, while indicating exemplary embodiments of the apparatus,systems and methods, are intended for purposes of illustration only andare not intended to limit the scope of the invention. These and otherfeatures, aspects, and advantages of the apparatus, systems and methodsof the present invention will become better understood from thefollowing description, appended claims, and accompanying drawings. Itshould be understood that the Figures are merely schematic and are notdrawn to scale. It should also be understood that the same referencenumerals are used throughout the Figures to indicate the same or similarparts.

The invention provides a system for waking a user up by a stimulus,wherein the stimulus is adapted to vary according to an intensity curve.A user interface is adapted to receive user preferences, such as adesired wake-up time and a preference indicator. The preferenceindicator indicates whether the user prefers to be more alert afterwaking up or to have a longer sleep. An alarm is used for providing astimulus to the user and a processor is used for determining a stimulusintensity curve for the alarm. Determining the stimulus intensity curveis based on at least the user preferences.

In an example, a memory unit is used for storing historic sleep data ofthe user. The historic sleep data includes historic real wake-up timesand corresponding historic intensity curves. The alarm stimulusintensity curve is then also based on the historic sleep data.

FIG. 1 shows a schematic representation of a system 100 for waking auser up. A user will indicate a set of user preferences 114, includingat what time they wish to wake up, termed a desired wake-up time 114 a,and whether they would prefer to have a longer time to sleep or feelmore alert in the morning, termed a preference indicator 114 b, on auser interface 102. There is also a memory unit 104 which storeshistoric sleeping data 112 of the user. A processor 106 then determinesan intensity curve 107 based on the historic sleeping data 112 and theuser preferences 114. The intensity curve is sent to an alarm 108 toprovide a stimulus to wake up the user. Once the user wakes up, the realwake-up time 110 of the user and the intensity curve 107 is stored inthe memory unit 104 as historic sleep data 112.

The system 100 could be part of a mobile phone, where the user interface102 is part of an application downloaded by the user on the mobilephone. The phone memory 104 and phone processor 106 could be used todetermine the intensity curve 107. The application could thencommunicate with an external alarm 108, such as a wake-up light, or thephone could use the built-in speaker as the alarm 108, where the volumeof the alarm is dependent on the intensity curve 107. The applicationcould also determine two different curves, one for an external wake-uplight and one for the built-in speaker.

FIGS. 2A and 2B show graphical representations of the intensity curves107. The stimulus may vary from a minimum value to a maximum value overa time period according to the stimulus intensity curve.

In conventional alarms 108, sound is used as a stimulus to wake up auser. Alternatively, light can also be used a stimulus, such as inwake-up lights, which increase the light intensity near or at thedesired wake-up time, creating a natural wake-up experience.

It is expected that there is no correlation between light intensitycurves 107 and sleep patterns, i.e. sleep stages, depth of sleep or EEGsignals. However, there is a clear correlation between the length of thewake-up light curve 107 and the alertness in the morning: longer lightcurves 107 lead to a more alert state, while the use of shorter lightcurves 107 leads to more sleepiness.

It is also known that longer light curves 107 increase the chance ofwaking up too early and having a larger variability in the wake-upmoment itself. Shorter light curves 107 on the other hand will wake uppeople closer to the desired wake-up time 114 a, meaning the duration ofsleep is maximized, but the chance of oversleeping increases.

A personalized setting prevents or at least diminishes thesedisadvantages while maintaining the natural wake-up experience andimproving the well-being when waking up for the day ahead.

This means a personalized balance between a more alert wake-upexperience, but shorter sleep i.e., waking up too early (with longcurves) and a longer night, so possibly a better overall satisfied sleepexperience, but a less alert wake-up experience (with short curves).

The personalized balance helps to overcome the negative effects on theuser's satisfaction of waking up too early or too late with the rightalgorithm based on the personal user's preferences 114. It also allowsthe user to select an option (with long curves) which reduces theprobability of oversleeping.

FIG. 2A shows a graphical representation of two different intensitycurves 107. If a user wants to wake up in a more alert state, it may bebeneficial to have a longer intensity curve 107 which starts earlier 202a, but may have a higher probability of waking the user up early. If thesame user wants to have a longer sleep on a different day, an intensitycurve 107 with a later start 202 b may provide the user with a longersleep, but with the possibility of a less alert wake-up experience.

FIG. 2B shows a second graphical representation of two differentintensity curves 107 with different peak light intensities 204. A usermay be waking up earlier than expected due an intensity curve 107 with ahigh peak light intensity 204 a. It may be beneficial to reduce the peaklight intensity to 204 b, such that the light intensity during which theuser typically wakes up happens later in time, closer to the desiredwake-up time 114 a.

There may also be separate intensity curves 107 while also the lightcolor is modulated, when using a wake-up light. For example, the lightcolor could start with a red tone and move to yellow and white tonesnear the desired wake-up time 114 a. The intensity curves 107 couldsimulate a sunrise.

FIG. 3 shows a second schematic representation of a system 100 forwaking a user up. Similarly to FIG. 1, the user interface 102 isconfigured to receive the user preferences 114. Additionally, the userinterface 102 can be further adapted to find the level of alertness forthe user at the wake-up time. The level of alertness may be assessed byusing the KSS (Karolinska Sleepiness Scale). For example, the userinterface 102 could ask the user a question when the user wakes up tofind the KSS score 302 of the user. The data can then stored as historicsleep data 112 in the memory unit 104.

Any other user indication relating to their satisfaction of theirwake-up experience may be used. There may be one or more questions forthe user to respond to, in order to assess their satisfaction level. Thespecific example of the KSS score is described below, simply by way ofexample.

The preference indicator 114 b can then be determined by asking the userwhether they prefer a better KSS score 302 with more chance to wake upearly or less chance to wake up early and a lower KSS score.

The user may also indicate the real wake-up time 110 on the userinterface 102. Alternatively an external sensor 310, such as a motionsensor, can indicate the real wake-up time 110.

The processor 106 predicts, based on the historic sleep data 112 for anumber of reference stimulus intensity curves 308, the likelihood of auser waking up early 306 and the most likely KSS score 304 the user willexperience at wake-up. This information is used in combination with theselected user preference 114 b to determine the most suitable intensitycurve 107.

The historic sleep data 112 may include the real wake-up time 110 forthe user every morning, the past intensity curves 107 and the historicKSS scores 302. The memory unit 104 may also contain the referencestimulus intensity curves 308.

The processor 106 can also take into account the measured amount oflight or even the expected amount of light in the bedroom due to the sunrising by using ambient light sensors.

Thus, many different types and combinations of sensors 310 could be usedto aid the processor 106 in determining an intensity curve 107. Thesensors 310 include, but are not limited to: a motion sensor for sensingwhen the user wakes up, an ambient light sensor, a temperature sensor oran ambient sound sensor (microphone). The data from the sensors 310 canbe saved on the memory unit 104 as historic sleep data 112. The datafrom these sensors 310 can be used in combination with the historicsleep data to find the ideal intensity curve 107 for the user fordifferent experiences, such as when the blinds are left open during thenight. For example if the user seems to wake up as soon as a certainthreshold of ambient light or ambient sound occurs, the intensity curve107 could be determined by the processor 106 such that the threshold isnot passed before the desired wake-up time 114 a.

In another example, the user's amount of time in bed and temperature inthe bedroom may also be determined using motion sensors andthermometers. The user may be more likely to wake up early at certaintemperature ranges or during longer sleep duration, so the intensitycurve 107 may be shortened in these circumstances.

The processor 106 could trigger a wake-up light alarm 108 and a speaker108 simultaneously with different intensity curves 108. The curve forthe wake-up light 108 could be determined, in part, by an ambient lightand/or the predicted ambient light at the desired wake-up time 114 a.The intensity curve 107 for the speaker 108 could be determined, inpart, from the ambient sound sensed by a microphone.

Then, based on the user preferences 114, the historical sleep data 112and the data from the sensors 310, the processor chooses the appropriatestart time 202, shape and peak intensity 204 of the intensity curve 107for the next wake-up cycle.

It is a fully adaptive and smart control algorithm to optimize thepersonal wake-up experience.

The historical sleep data 112 may also be used to alter and/or addreference stimulus intensity curves 308. For example, the curves withthe associated KSS scores 302 and real wake-up times 110 which areclosest to the preference 114 b indicated by the user may be used infuture as the reference stimulus intensity curves 308.

If the application is downloaded on a wearable device, such as a smartwatch, the sensors 310 of the wearable device could be used foradditional data. For example, the gyroscope of the device could be usedto sense movement of the user. A heart rate monitor in conjunction withother sensors, such as a microphone and/or gyroscope, could be used tofind the sleep stage the user is in. The sleep stage could then be usedby the processor 106 of the wearable device to determine an intensitycurve 107. For example, it may not be desirable to exceed a certainintensity of light and/or sound when the user is in deep sleep.

FIG. 4 shows a method used by a processor 106 to determine an intensitycurve 107 to be generated by an alarm 108. The method comprises firstreceiving user preferences from the user in steps 402 and 406. Receivingthe user preferences comprises receiving a desired wake-up time, in step402, and receiving a preference indicator, in step 406, which indicateswhether the user prefers to be more alert after waking up or to have alonger sleep. The processor 106 also reads historic sleep data from amemory unit in step 404. Based on the user preferences and the historicsleep data, the processor then generates a stimulus intensity curve instep 408. The alarm is then actuated in step 410 to wake up the user. Areal wake-up time is then determined, in step 412, at the time the userwakes up in response to the corresponding stimulus from the alarm, andthe real wake-up time and the corresponding stimulus intensity curve arestored in a memory unit as historic sleep data in step 414.

FIGS. 2A and 2B show a gradual increase in the stimulus intensity, withincreasing steepness (gradient) over time, so that there is a more rapidincrease in intensity as the desired wake-up time is approached. Othershapes for the intensity curve are possible. For example, there may beflat regions and more abrupt step increases in intensity. There may forexample be a step increase in intensity at the end of the curve toensure a more reliable wake-up at the desired wake-up time, if the userhas not already woken up (and turned off the alarm) by then.

For color control, there may be a decrease in intensity for some colorsand an increase in intensity for others. The overall intensity curve ofthe stimulus (i.e., light) may therefore have multiple stimuluscomponents which combine to create the desired overall effect.

The determination of the intensity curve may involve adapting the shapein a more complex way than the simple stretching represented in FIGS. 2Aand 2B.

The example described above makes use of historical information so thatthe response of the individual user to different alarm stimuli may betaken into account. However, in a most basic implementation there is aset of alarm stimuli, i.e. intensity curves, and the processor selectsthe most appropriate an intensity curve based on the preferenceindicator.

As discussed above, the system makes use of processor to perform thedata processing. The processor can be implemented in numerous ways, withsoftware and/or hardware, to perform the various functions required. Theprocessor typically employs one or more microprocessors that may beprogrammed using software (e.g., microcode) to perform the requiredfunctions. The processor may be implemented as a combination ofdedicated hardware to perform some functions and one or more programmedmicroprocessors and associated circuitry to perform other functions.

Examples of circuitry that may be employed in various embodiments of thepresent disclosure include, but are not limited to, conventionalmicroprocessors, application specific integrated circuits (ASICs), andfield-programmable gate arrays (FPGAs).

In various implementations, the processor may be associated with one ormore storage media such as volatile and non-volatile computer memorysuch as RAM, PROM, EPROM, and EEPROM. The storage media may be encodedwith one or more programs that, when executed on one or more processorsand/or controllers, perform the required functions. Various storagemedia may be fixed within a processor or controller or may betransportable, such that the one or more programs stored thereon can beloaded into a processor.

Variations to the disclosed embodiments can be understood and effectedby those skilled in the art in practicing the claimed invention, from astudy of the drawings, the disclosure and the appended claims. In theclaims, the word “comprising” does not exclude other elements or steps,and the indefinite article “a” or “an” does not exclude a plurality. Asingle processor or other unit may fulfill the functions of severalitems recited in the claims. The mere fact that certain measures arerecited in mutually different dependent claims does not indicate that acombination of these measures cannot be used to advantage. If a computerprogram is discussed above, it may be stored/distributed on a suitablemedium, such as an optical storage medium or a solid-state mediumsupplied together with or as part of other hardware, but may also bedistributed in other forms, such as via the Internet or other wired orwireless telecommunication systems. If the term “adapted to” is used inthe claims or description, it is noted the term “adapted to” is intendedto be equivalent to the term “configured to”. Any reference signs in theclaims should not be construed as limiting the scope.

1. A system for waking a user up by a stimulus, wherein the stimulus isadapted to vary according to an intensity curve, comprising: a userinterface adapted to receive user preferences, wherein the userpreferences comprise: a desired wake-up time; and a preferenceindicator, wherein the preference indicator indicates whether the userprefers; to be more alert after waking up with a higher probability ofwaking up earlier than the desired wake up time or to have a longersleep by being closer to the desired wake up time with a higherprobability of being less alert after waking up; an alarm for providinga stimulus to the user wherein the stimulus varies according to anintensity curve from a minimum value to a maximum value over a timeperiod; and a processor for determining a suitable start time and peakintensity of the intensity curve for the alarm based on the userpreferences.
 2. A system as claimed in claim 1, further comprising amemory unit for storing historic sleep data of the user comprising atleast historic real wake-up times and corresponding historic intensitycurves, and wherein the processor for determining an intensity curve forthe alarm further based on the historic sleep data.
 3. A system asclaimed in claim 2, wherein the user interface is further adapted todetermine a Karolinska Sleepiness Scale, KSS, score or othersatisfaction level of the user after waking up and store the score orlevel in the memory unit as historic sleep data.
 4. A system as claimedin claim 3, wherein the determining of an intensity curve for the alarmby the processor further comprises: estimating a KSS score or othersatisfaction level for the user, at the desired wake-up time, for aplurality of reference stimulus intensity curves based on the historicsleep data of the user; estimating the likelihood of the user waking upearly, compared to the desired wake-up time, for a plurality ofreference stimulus intensity curves from the historic sleep data; anddetermining an intensity curve based on analysis of the estimated KSSscore or satisfaction level, the estimated likelihood of the user wakingup early and the preference indicator.
 5. A system as claimed in claim1, wherein the alarm is a wake-up light and the intensity curvemodulates the intensity and/or color of the light.
 6. A system asclaimed in claim 5 wherein the intensity curve simulate a sunrise.
 7. Asystem as claimed in claim 1, further comprising at least one sensor orinput device for receiving sensor data or input data, wherein theprocessor is adapted to use the sensor data to determine the intensitycurve, wherein the sensor or input device comprises one or more of: amotion sensor for sensing when the user wakes up; a sensor for detectingwhen the user falls asleep; an ambient light sensor; a temperaturesensor; a user input device; and an ambient sound sensor.
 8. A system asclaimed in claim 1, wherein the user interface is further adapted toreceive the real wake-up time from the user.
 9. A method for determiningan intensity curve for a stimulus to be generated by an alarm whereinthe stimulus varies according to the intensity curve from a minimumvalue to a maximum value over a time period, comprising: receiving userpreferences, wherein the user preferences comprise: a desired wake-uptime; and a preference indicator which indicates whether the userprefers; to be more alert after waking up with a higher probability ofwaking up earlier than the desired wake up time or to have a longersleep by being closer to the desired wake up time with a higherprobability of being less alert after waking up; determining a suitablestart time and peak intensity of the intensity curve based on the userpreferences.
 10. A method as claimed in claim 9, further comprisingstoring historic sleep data of the user comprising at least historicreal wake-up times and corresponding historic intensity curves, whereindetermining an intensity curve is further based on the historic sleepdata.
 11. A method as claimed in claim 9, further comprising:determining a Karolinska Sleepiness Scale, KSS, score or othersatisfaction level of the user after waking up; and storing the KSSscore or other satisfaction level in the memory unit as historic sleepdata.
 12. A method as claimed in claim 11, wherein the determining of anintensity curve further comprises: estimating a KSS score or othersatisfaction level, for the user at the desired wake-up time, for aplurality of reference stimulus intensity curves based on the historicsleep data of the user; estimating the likelihood of user waking upearly, compared to the desired wake up time, for a plurality ofreference stimulus intensity curves from the historic sleep data; anddetermining an intensity curve based on analyzing the estimated KSSscores or other satisfaction levels, the estimated likelihood of theuser waking up early and the preference indicator.
 13. A method asclaimed in claim 9, further comprising receiving sensing data from atleast one sensor or input data from an input device, wherein the sensoror input device comprises one or more of: a motion sensor for sensingwhen the user wakes up; a sensor for detecting when the user fallsasleep; an ambient light sensor; a temperature sensor; a user inputdevice; an ambient sound sensor, and wherein the method furthercomprises storing the sensing data or input data as part of the historicsleep data.
 14. A computer program comprising computer program codemeans which is adapted, when said computer program is run on a computer,to implement the method of claim 9.